Data Quality Solutions to Improve Healthcare Data
Patient Care Begins With Accurate Patient Information
How Melissa Helps Healthcare
Melissa marries 30+ years of address expertise and contact data quality with AI to drive discovery in healthcare and life sciences. Our solutions clean up EMR/EHR records, and get data compliant and interoperable for greater use, better visualization and new insight. As a HIPAA/HITECH and SOC 2 Compliant solutions provider, we work hard to ensure the privacy and security of your mission-critical data. Work with us to:
Reduce operational costs & waste
Improve patient care & emergency preparedness
Realize new intellectual property & revenue from clinical practice data
Gain advanced insight & make new discoveries
Solutions for Quality Patient Data
Our solutions keep patient and clinical data clean and accurate to help you improve healthcare operations, better understand your patients, make new discoveries, and lower costs.
PATIENT ONBOARDING
Validate, correct and standardize patient contact data at point-of-entry – name, address, email and phone – to improve onboarding and minimize risk. Autocomplete addresses as you type.
REMOVE DUPLICATE RECORDS
Match, merge and purge duplicate patient records across households, facilities and time to minimize patient frustration, billing and claim errors, and legal liabilities.
ENSURE TIMELY PAYMENTS
Update the addresses of your customers as they move to ensure invoices arrive in a timely manner and claims are submitted with accurate patient information to avoid denials.
UNDERSTAND SERVICE TERRITORIES
Add location intelligence like exact drive time and true distance between your patients or new subscribers and your facilities. Get geographic info for a better understanding of the areas you service.
IMPROVE HEALTH INITIATIVES
Add precise demographic data to your records like age, sex, race and income to help ensure better resource allocation, patient care and public policy.
AI-ENABLED SEMANTIC TECHNOLOGY
Check, verify, append and autocomplete pharmaceutical names, variants, dosages and spellings. Clean, connect and harmonize multiple datasets to create one unified resource. Enable clinical insight and discovery with machine reasoning.
Case Study: HealthLink Dimensions
HealthLink manages one of the largest databases of active practicing physicians and needed a solution that would clean and standardize this massive, multisourced dataset.
View HealthLink Case Study
Minimized labor costs
Fully-automated
contact data cleansing
Now catches
errors in real time
Easily integrated into
existing .NET and SQL processes
Used GeoCoder to
find nearby physicians in network
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Chris Lloyd
Director of Database Services"GeoCoder allows us to maintain multiple addresses for the same physician even when we are receiving and loading the data from more than one source. We use the mileage distance between addresses to write proprietary business rules to locate physicians that practice in multiple locations, and even across state borders."
Case Study: CalOptima
Find out how CalOptima, the second largest health insurer in Orange County, migrated 422,000 members, 5,800 physicians, and 24 hospitals into one data warehouse with the help of Melissa’s Data Quality Components for SSIS.
View CalOptima Case Study
Easy implementation
with SSIS
Used GeoCoder to find
nearby physicians in network
Better knowledge
of member locations
Reduced returned
mail costs
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Osvaldo Cruz
Data Warehouse Architect"Our main objective was to add value to the data produced for business users. Having conformed and integrated data is valuable, but the added value of recognizing valid addresses is significant. One of the cost-driven indicators is returned mail and missing communication with members."